scholarly journals Contribution of insurance data to cost assessment of coastal flood damage to residential buildings: insights gained from Johanna (2008) and Xynthia (2010) storm events

2013 ◽  
Vol 1 (2) ◽  
pp. 829-854
Author(s):  
C. André ◽  
D. Monfort ◽  
M. Bouzit ◽  
C. Vinchon
Keyword(s):  
Residential Buildings ◽  
Flood Damage ◽  
Storm Events ◽  
Methodological Issues ◽  
Damage Functions ◽  
Damage Modelling ◽  
Future Events ◽  
Paper Format ◽  
Insurance Data ◽  
Do So

Abstract. There are a number of methodological issues involved in assessing damage caused by natural hazards. The first is the lack of data, due to the rarity of events and the widely different circumstances in which they occur. Thus, historical data, albeit scarce, should not be neglected when seeking to build ex-ante risk management models. This article analyses the input of insurance data for two recent severe coastal storm events, to examine what causal relationships may exist between hazard characteristics and the level of damage incurred by residential buildings. To do so, data was collected at two levels: from lists of about 4000 damage records, 358 loss adjustment reports were consulted, constituting a detailed damage database. The results show that for flooded residential buildings, over 75% of reconstruction costs are associated with interior elements, damage to structural components remaining very localised and negligible. Further analysis revealed a high scatter between costs and water depth, suggesting that uncertainty remains high in drawing up damage functions with insurance data alone. Due to the paper format of the loss adjustment reports and the lack of harmonisation between their contents, the collection stage called for a considerable amount of work. For future events, establishing a standardised process for archiving damage information could significantly contribute to the production of such empirical damage functions. Nevertheless, complementary sources of data on hazards and asset vulnerability parameters, will definitely still be necessary for damage modelling and multivariate approaches, crossing insurance data with external material, should also be deeper investigated.

scholarly journals Contribution of insurance data to cost assessment of coastal flood damage to residential buildings: insights gained from Johanna (2008) and Xynthia (2010) storm events

2013 ◽  
Vol 13 (8) ◽  
pp. 2003-2012 ◽  
Author(s):  
C. André ◽  
D. Monfort ◽  
M. Bouzit ◽  
C. Vinchon
Keyword(s):  
Residential Buildings ◽  
Flood Damage ◽  
Storm Events ◽  
Methodological Issues ◽  
Damage Functions ◽  
Damage Modelling ◽  
Future Events ◽  
Paper Format ◽  
Insurance Data ◽  
Do So

Abstract. There are a number of methodological issues involved in assessing damage caused by natural hazards. The first is the lack of data, due to the rarity of events and the widely different circumstances in which they occur. Thus, historical data, albeit scarce, should not be neglected when seeking to build ex-ante risk management models. This article analyses the input of insurance data for two recent severe coastal storm events, to examine what causal relationships may exist between hazard characteristics and the level of damage incurred by residential buildings. To do so, data was collected at two levels: from lists of about 4000 damage records, 358 loss adjustment reports were consulted, constituting a detailed damage database. The results show that for flooded residential buildings, over 75% of reconstruction costs are associated with interior elements, with damage to structural components remaining very localised and negligible. Further analysis revealed a high scatter between costs and water depth, suggesting that uncertainty remains high in drawing up damage functions with insurance data alone. Due to the paper format of the loss adjustment reports, and the lack of harmonisation between their contents, the collection stage called for a considerable amount of work. For future events, establishing a standardised process for archiving damage information could significantly contribute to the production of such empirical damage functions. Nevertheless, complementary sources of data on hazards and asset vulnerability parameters will definitely still be necessary for damage modelling; multivariate approaches, crossing insurance data with external material, should also be investigated more deeply.

Flood damage assessment to economic activities: implementation and transferability of French methodology

2021 ◽  
Author(s):  
Frédéric Grelot ◽  
Marta Galliani ◽  
Pauline Bremond ◽  
Daniela Molinari ◽  
Lilian Pugnet ◽  
...  
Keyword(s):  
Residential Buildings ◽  
Flood Damage ◽  
Economic Activities ◽  
Damage Functions ◽  
Flood Prevention ◽  
Damage Modelling ◽  
French Case ◽  
Damage Data ◽  
The City

<p>Since 2010, a national method is available in France for multi-criteria analysis of flood prevention projects. The method uses national damage functions to estimate losses to the different exposed items, including economic activities. Despite the business sector suffers significant losses in case of flood, flood damage modelling to businesses is less advanced than for other exposed sectors, as e.g. residential buildings. Reasons are many and include: the high variability of activities types composing this sector and then the difficulty of standardisation (above all when contents are considered), and the lack of data to understand and quantify damage and validate existing modelling tools. The collection of damage data in two case studies, in France and in Italy, and the collaboration between two research groups in the two countries allowed to study the applicability, the validity, and the transferability of the French damage functions for economic activities to Italy. Firstly, the functions were tested and validated in a French case study, i.e. the flood that affected the Île-de-France Region in 2016. This validation exercise faced the problem of working with few information about the identity of the activities, and propose a solution; moreover, it allowed to verify the actual availability of input data to implement the functions in France and pointed out the paucity of information to validate the methodology. Testing the functions in a foreign case study, i.e. the flood occurred in 2002 in Italy in the city of Lodi, allowed instead to verify the transferability of the method.</p>

scholarly journals How reliable are projections of future flood damage?

2011 ◽  
Vol 11 (12) ◽  
pp. 3293-3306 ◽  
Author(s):  
P. Bubeck ◽  
H. de Moel ◽  
L. M. Bouwer ◽  
J. C. J. H. Aerts
Keyword(s):  
Land Use ◽  
Flood Damage ◽  
Flood Risk Management ◽  
Future Research ◽  
River Rhine ◽  
Damage Functions ◽  
Damage Modelling ◽  
Asset Values ◽  
Over Time ◽  
Modelling Approaches

Abstract. Flood damage modelling is an important component in flood risk management, and several studies have investigated the possible range of flood damage in the coming decades. Generally, flood damage assessments are still characterized by considerable uncertainties in stage-damage functions and methodological differences in estimating exposed asset values. The high variance that is commonly associated with absolute flood damage assessments is the reason for the present study that investigates the reliability of estimates of relative changes in the development of potential flood damage. While studies that estimate (relative) changes in flood damage over time usually address uncertainties resulting from different projections (e.g. land-use characteristics), the influence of different flood damage modelling approaches on estimates of relative changes in the development of flood damage is largely unknown. In this paper, we evaluate the reliability of estimates of relative changes in flood damage along the river Rhine between 1990 and 2030 in terms of different flood-damage modelling approaches. The results show that relative estimates of flood damage developments differ by a factor of 1.4. These variations, which result from the application of different modelling approaches, are considerably smaller than differences between the approaches in terms of absolute damage estimates (by a factor of 3.5 to 3.8), or than differences resulting from land-use projections (by a factor of 3). The differences that exist when estimating relative changes principally depend on the differences in damage functions. In order to improve the reliability of relative estimates of changes in the development of potential flood damage, future research should focus on reducing the uncertainties related to damage functions.

scholarly journals Is flow velocity a significant parameter in flood damage modelling?

2009 ◽  
Vol 9 (5) ◽  
pp. 1679-1692 ◽  
Author(s):  
H. Kreibich ◽  
K. Piroth ◽  
I. Seifert ◽  
H. Maiwald ◽  
U. Kunert ◽  
...  
Keyword(s):  
Flow Velocity ◽  
Water Depth ◽  
Structural Damage ◽  
Residential Buildings ◽  
Flood Damage ◽  
Damage Models ◽  
Damage Modelling ◽  
Impact Parameters ◽  
A Minor ◽  
The Impact

Abstract. Flow velocity is generally presumed to influence flood damage. However, this influence is hardly quantified and virtually no damage models take it into account. Therefore, the influences of flow velocity, water depth and combinations of these two impact parameters on various types of flood damage were investigated in five communities affected by the Elbe catchment flood in Germany in 2002. 2-D hydraulic models with high to medium spatial resolutions were used to calculate the impact parameters at the sites in which damage occurred. A significant influence of flow velocity on structural damage, particularly on roads, could be shown in contrast to a minor influence on monetary losses and business interruption. Forecasts of structural damage to road infrastructure should be based on flow velocity alone. The energy head is suggested as a suitable flood impact parameter for reliable forecasting of structural damage to residential buildings above a critical impact level of 2 m of energy head or water depth. However, general consideration of flow velocity in flood damage modelling, particularly for estimating monetary loss, cannot be recommended.

Verification of flood damage modelling using insurance data

2013 ◽  
Vol 68 (2) ◽  
pp. 425-432 ◽  
Author(s):  
Q. Zhou ◽  
T. E. Panduro ◽  
B. J. Thorsen ◽  
K. Arnbjerg-Nielsen
Keyword(s):  
Risk Model ◽  
Flood Damage ◽  
Model Verification ◽  
Urban Drainage ◽  
Hazard Maps ◽  
Damage Modelling ◽  
Damage Costs ◽  
Data Collection And Analysis ◽  
Inundation Modelling ◽  
Insurance Data

This paper presents the results of an analysis using insurance data for damage description and risk model verification, based on data from a Danish case. The results show that simple, local statistics of rainfall are not able to describe the variation in individual cost per claim, but are, however, feasible for modelling the overall cost per day. The study also shows that in combining the insurance and regional data it is possible to establish clear relationships between occurrences of claims and hazard maps. In particular, the results indicate that with improvements to data collection and analysis, improved prediction of damage costs will be possible, for example based also on socioeconomic variables. Furthermore, the paper concludes that more collaboration between scientific research and insurance agencies is needed to improve inundation modelling and economic assessments for urban drainage designs.

scholarly journals Are new open building data useful for flood vulnerability modelling?

2020 ◽  
Author(s):  
Marco Cerri ◽  
Max Steinhausen ◽  
Heidi Kreibich ◽  
Kai Schröter
Keyword(s):  
Residential Buildings ◽  
Open Data ◽  
Residential Building ◽  
Predictive Performance ◽  
Flood Damage ◽  
Building Vulnerability ◽  
Damage Functions ◽  
Data Set ◽  
Flood Vulnerability ◽  
Spatial Measures

Abstract. Flood risk modelling aims to quantify the probability of flooding and the resulting consequences for exposed elements. The assessment of flood damage is a core task that requires the description of complex flood damage processes including the influences of flooding intensity and vulnerability characteristics. Multi-variable modelling approaches are better suited for this purpose than simple stage-damage functions. However, multi-variable flood vulnerability models also often have problems to predict damage for regions other than those for which they have been developed. A transfer of vulnerability models usually results in a drop of model predictive performance. Here we investigate the question of whether data from the open data source OpenStreetMap is suitable to model flood vulnerability of residential buildings and whether the underlying standardized data model is helpful to transfer models across regions. We develop a new data set by calculating numerical spatial measures for residential building footprint geometries and combine these variables with an empirical data set of observed flood damage. From this data set random forest regression models are learned using regional sub-sets and are tested for predicting flood damage in other regions. This regional split-sample validation approach reveals that the predictive performance of models based on OpenStreetMap data is comparable to alternative multi-variable models, which use comprehensive and detailed information about preparedness, socio-economic status and other aspects of residential building vulnerability. However, our results show that using numerical spatial measures derived from OpenStreetMap building geometries does not resolve all problems of model transfer. Still, we conclude that these variables are useful proxies for flood vulnerability modelling, because these data are consistent, openly accessible, and thus make it easier and more cost-effective to transfer vulnerability models to other regions.

TIME TRAVEL TESTIMONY AND THE ‘JOHN TITOR’ FIASCO

Think ◽  
2010 ◽  
Vol 9 (26) ◽  
pp. 7-20
Author(s):  
Alasdair Richmond
Keyword(s):  
Civil War ◽  
Time Travel ◽  
Nuclear War ◽  
Future Events ◽  
Do So

Around 1998, internet postings began appearing under the alias ‘Timetravel_0’. This alias was later replaced by ‘John Titor’, and it's as such I'll designate the posts' author(s). Remarkably, Titor claimed to have time-travelled from 2036 on a mission to retrieve an IBM 5100 in 1975. Titor refrained from public appearances and any evidence for his story remains web-bound but before closing shop c. March 24th 2001, he described various future events, e.g.: Y2K is a disaster. Many people die on the highways when they freeze to death trying to get to warmer weather.Cancellation of the Olympics after 2004 due to world conflict.America will soon be engaged in civil war with itself; a civil war that we'll see the beginnings of during 2004 and 2005, escalating until it is indisputable by 2008.(Y2K predictions diminished after 1st Jan 2000. One wonders how America could suffer civil war other than with itself or do so disputably for three years. Titorists still found signs of civil war in 2008.) This equivocal civil war fizzles until global nuclear war kills three billion people in 2015. (On the plus side, hats are popular in 2036.)

scholarly journals Adaptability and transferability of flood loss functions in residential areas

2013 ◽  
Vol 1 (4) ◽  
pp. 3485-3527 ◽  
Author(s):  
H. Cammerer ◽  
A. H. Thieken ◽  
J. Lammel
Keyword(s):  
Flood Risk ◽  
Residential Buildings ◽  
Model Development ◽  
Loss Functions ◽  
Residential Areas ◽  
Damage Functions ◽  
Residential Sector ◽  
Geographical Regions ◽  
Flood Loss ◽  
Loss Data

Abstract. Flood loss modeling is an important component within flood risk assessments. Traditionally, stage-damage functions are used for the estimation of direct monetary damage to buildings. Although it is known that such functions are governed by large uncertainties, they are commonly applied – even in different geographical regions – without further validation, mainly due to the lack of data. Until now, little research has been done to investigate the applicability and transferability of such damage models to other regions. In this study, the last severe flood event in the Austrian Lech Valley in 2005 was simulated to test the performance of various damage functions for the residential sector. In addition to common stage-damage curves, new functions were derived from empirical flood loss data collected in the aftermath of recent flood events in the neighboring Germany. Furthermore, a multi-parameter flood loss model for the residential sector was adapted to the study area and also evaluated by official damage data. The analysis reveals that flood loss functions derived from related and homogenous regions perform considerably better than those from more heterogeneous datasets. To illustrate the effect of model choice on the resulting uncertainty of damage estimates, the current flood risk for residential areas was assessed. In case of extreme events like the 300 yr flood, for example, the range of losses to residential buildings between the highest and the lowest estimates amounts to a factor of 18, in contrast to properly validated models with a factor of 2.3. Even if the risk analysis is only performed for residential areas, more attention should be paid to flood loss assessments in future. To increase the reliability of damage modeling, more loss data for model development and validation are needed.

scholarly journals Uncertainties in Coastal Flood Risk Assessments in Small Island Developing States

2019 ◽  
Author(s):  
Matteo U. Parodi ◽  
Alessio Giardino ◽  
Ap van Dongeren ◽  
Stuart G. Pearson ◽  
Jeremy D. Bricker ◽  
...  
Keyword(s):  
Flood Risk ◽  
Input Data ◽  
Flood Damage ◽  
Small Island ◽  
Small Island Developing States ◽  
Damage Functions ◽  
Current Time ◽  
Coastal Flood ◽  
Coastal Flood Risk ◽  
The Impact

Abstract. Considering the likely increase of coastal flooding in Small Island Developing States (SIDS), coastal managers at the local and global level have been developing initiatives aimed at implementing Disaster Risk Reduction (DRR) measures and adapting to climate change. Developing science-based adaptation policies requires accurate coastal flood risk (CFR) assessments, which are often subject to the scarcity of sufficiently accurate input data for insular states. We analysed the impact of uncertain inputs on coastal flood damage estimates, considering: (i) significant wave height, (ii) storm surge level and (iii) sea level rise (SLR) contributions to extreme sea levels, as well as the error-driven uncertainty in (iv) bathymetric and (v) topographic datasets, (vi) damage models and (vii) socioeconomic changes. The methodology was tested through a sensitivity analysis using an ensemble of hydrodynamic models (XBeach and SFINCS) coupled with an impact model (Delft-FIAT) for a case study at the islands of São Tomé and Príncipe. Model results indicate that for the current time horizon, depth damage functions (DDF) and digital elevation model (DEM) dominate the overall damage estimation uncertainty. We find that, when introducing climate and socioeconomic uncertainties to the analysis, SLR projections become the most relevant input for the year 2100 (followed by DEM and DDF). In general, the scarcity of reliable input data leads to considerable predictive error in CFR assessments in SIDS. The findings of this research can help to prioritise the allocation of limited resources towards the acquisitions of the most relevant input data for reliable impact estimation.

scholarly journals Estimation of an absolute flood damage curve based on an Austrian case study under a dam breach scenario

2010 ◽  
Vol 10 (4) ◽  
pp. 881-894 ◽  
Author(s):  
F. Prettenthaler ◽  
P. Amrusch ◽  
C. Habsburg-Lothringen
Keyword(s):  
Future Development ◽  
Damage Assessment ◽  
Field Data ◽  
Flood Damage ◽  
Damage Function ◽  
Damage Potential ◽  
Dam Breach ◽  
Damage Functions ◽  
Austrian Case

Abstract. To date, in Austria no empirical assessment of absolute damage curves has been realized on the basis of detailed information on flooded buildings due to a dam breach, presumably because of the lack of data. This paper tries to fill this gap by estimating an absolute flood-damage curve, based on data of a recent flood event in Austria in 2006. First, a concise analysis of the case study area is conducted, i.e., the maximum damage potential is identified by using raster-based GIS. Thereafter, previous literature findings on existing flood-damage functions are considered in order to determine a volume-water damage function that can be used for further flood damage assessment. Finally, the flood damage function is cross validated and applied in prediction of damage potential in the study area. For future development of the estimated flood damage curve, and to aid more general use, we propose verification against field data on damage caused by natural waves in rivers.

Sign in / Sign up

Export Citation Format

Share Document